Small noise asymptotics for a stochastic growth model
By: Noah Williams.
Contributors: National Bureau of Economic Research.
Series: NBER working paper series ;; working paper 10194; Working paper series (National Bureau of Economic Research : Online) ;; working paper no. 10194.
Publisher: National Bureau of Economic Research
Published: 2003
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Subjects: Stochastic processes.; Economic development -- Mathematical models.
Description: "We develop analytic asymptotic methods to characterize time series properties of nonlinear dynamic stochastic models.  We focus on a stochastic growth model which is representative of the models underlying much of modern macroeconomics.  Taking limits as the stochastic shocks become small, we derive a functional central limit theorem, a large deviation principle, and a moderate deviation principle.  These allow us to calculate analytically the asymptotic distribution of the capital stock, and to obtain bounds on the probability that the log of the capital stock will differ from its deterministic steady state level by a given amount.  This latter result can be applied to characterize the probability and frequency of large business cycles.  We then illustrate our theoretical results through some simulations.  We find that our results do a good job of characterizing the model economy, both in terms of its average behavior and its occasional large cyclical fluctuations"--National Bureau of Economic Research web site.
Notes: Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 1/27/2005.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.